code: def run_example(cdc_settings):
      event_mentions_topics = Topics()
      event_mentions_topics.create_from_file(
          str(
              LIBRARY_ROOT
              / "datasets"
              / "ecb"
              / "ecb_all_event_mentions.json"
          )
      )
  
      event_clusters = None
      if cdc_settings.event_config.run_evaluation:
          logger.info("Running event coreference resolution")
          event_clusters = run_event_coref(
              event_mentions_topics, cdc_settings
          )
  
      entity_mentions_topics = Topics()
      entity_mentions_topics.create_from_file(
          str(
              LIBRARY_ROOT
              / "datasets"
              / "ecb"
              / "ecb_all_entity_mentions.json"
          )
      )
      entity_clusters = None
      if cdc_settings.entity_config.run_evaluation:
          logger.info("Running entity coreference resolution")
          entity_clusters = run_entity_coref(
              entity_mentions_topics, cdc_settings
          )
  
      return event_clusters, entity_clusters
  
file_path: nlp-architect/examples/cross_doc_coref/cross_doc_coref_sieves.py
imports: import logging
  from typing import List
  from nlp_architect import LIBRARY_ROOT
  from nlp_architect.common.cdc.cluster import Clusters
  from nlp_architect.common.cdc.topics import Topics
  from nlp_architect.data.cdc_resources.relations.referent_dict_relation_extraction import ReferentDictRelationExtraction
  from nlp_architect.data.cdc_resources.relations.relation_types_enums import RelationType
  from nlp_architect.data.cdc_resources.relations.wikipedia_relation_extraction import WikipediaRelationExtraction
  from nlp_architect.data.cdc_resources.relations.word_embedding_relation_extraction import WordEmbeddingRelationExtraction
  from nlp_architect.models.cross_doc_coref.sieves_config import EventSievesConfiguration, EntitySievesConfiguration
  from nlp_architect.models.cross_doc_coref.sieves_resource import SievesResources
  from nlp_architect.models.cross_doc_coref.system.sieves_container_init import SievesContainerInitialization
  from nlp_architect.models.cross_doc_sieves import run_event_coref, run_entity_coref
label_desc: Use image node_id 1 for calling a global function with example usage: run_example(cdc_settings) and returns: event_clusters,  entity_clusters